Characterization of European Carrot Genotypes Through Principal Components and Regression Analyses

Utilization of genetic resources in developing sustainable solutions to basic crop constraints have been suggested from time to time, but these genetic resources could not be exploited fully due to their inherent problems of large size and lack of sufficient evaluation and classification (CitationDahberg, 1995). Germplasm maintenance, evaluation, and characterization for economically important traits are prerequisite for genetic improvement program of any crop. This principal components approach could resolve several phenotypic measurements even of large collections into fewer, more interpretable, and more easily visualized dimensions. The investigation was conducted from Aug. 2007 to Jan. 2008 to characterize genotypes of European carrots (Daucus carota Linn.) with economic characters based on principal components and regression analysis. The effect and contribution of each character on root yield was measured. Principal components analysis characterized the genotypes into four principal components based on their total variation (83.86%). The first principal component accounted for more than 39% of the total variation and it is the combination of the characters root diameter, root weight, marketable root yield, core diameter, flesh thickness, shoulder thickness, and days to marketable maturity. To quantify the importance of each variable in predicting average root weight and marketable root yield, multiple linear regression models were developed. Model I indicated that average root weight can be predicted on the basis of leaf length, shoulder thickness, crown diameter, marketable root yield per plot, forking, and cracking percentage. Model II indicated that marketable root yield can be best predicted by shoulder thickness, crown diameter, root weight, and cracking percentage. Model I is suitable for estimation of total yield including marketable and nonmarketable roots; model II is best for the estimation of marketable yield.